Elastic scaling of data volume

ABSTRACT

Embodiments are directed towards a system and method for a cloud-based front end that may abstract and enable access to the underlying cloud-hosted elements and objects that may be part of a multi-tenant application, such as a search application. Search objects may be employed to access indexed objects. An amount of indexed data accessible to a user may be based on an index storage limit selected by the user, such that data that exceeds the index storage limit may continue to be indexed. Also, one or more projects can be elastically scaled for a user to provide resources that may meet the specific needs of each project.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation patent application of patentapplication Ser. No. 13/572,464 filed on Aug. 10, 2012, which claimspriority under 35 U.S.C. §119(e) to U.S. Provisional Patent ApplicationSer. No. 61/523,063 filed on Aug. 12, 2011, entitled “DATA VOLUMEMANAGEMENT”. The subject matter of all of the foregoing is incorporatedherein by reference in its entirety.

TECHNICAL FIELD

The invention is directed to providing services for use by a customer,and more particularly, to providing search services to the customer overa network with a cloud-based system.

BACKGROUND

Many companies install and maintain software for use on a variety ofdistributed systems that can range from a single computer for a smallbusiness to a collection of servers and a plurality of user computernodes for a large corporation. Also, the volume of data processed by anode in a small business can be a magnitude less than the volume of dataprocessed by a node in a large corporation. Further, at different timesthe amount of data to be indexed for searching and the need for speed tosearch the indexed data can vary.

Additionally, the type of data processed by large and small business canvary widely, such as sending and receiving messages, creating andstoring documents, hosting web sites, database searches, facilitatingonline transactions, and the like. Furthermore, the expense ofdeveloping and maintaining software that can handle the type and volumeof data processed by a large corporation can be substantially greaterthan the effort expended to do somewhat the same for a small business.Consequently, cloud-based systems that provide software as a service areincreasingly popular with different sizes of businesses having differentvolumes of data and types of data.

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting and non-exhaustive embodiments are described with referenceto the following drawings. In the drawings, like reference numeralsrefer to like parts throughout the various figures unless otherwisespecified.

For a better understanding, reference will be made to the followingDetailed Description, which is to be read in association with theaccompanying drawings, wherein:

FIG. 1 illustrates a system environment in which various embodiments maybe implemented;

FIG. 2A shows a rack of blade servers that may be included in variousembodiments;

FIG. 2B illustrates an embodiment of a blade server that may be includedin a rack of blade servers such as that shown in FIG. 2A;

FIG. 3 shows a mobile device that may be included in variousembodiments;

FIG. 4 illustrates a network device that may be included in variousembodiments;

FIG. 5 illustrates a system diagram showing an embodiment of a systemthat may be utilized to implement embodiments of processing, searchingand managing data volumes;

FIG. 6 illustrates a system diagram showing an alternative embodiment ofa system that may be utilized to implement embodiments of processing,searching and managing data volumes;

FIG. 7 illustrates a logical flow diagram generally showing oneembodiment of an overview process for initiating a project that employsembodiments of the system diagrams shown in FIGS. 5 and/or 6;

FIG. 8 illustrates a logical flow diagram generally showing oneembodiment of a process for enabling access to a determined volume ofdata and restricting access to incoming data that exceeds the determinedvolume;

FIG. 9 illustrates a logical flow diagram generally showing oneembodiment of a process for managing an overflow index store;

FIG. 10 illustrates a logical flow diagram generally showing oneembodiment of a process for enabling a project owner to invite anotheruser into the project;

FIG. 11 illustrates a logical flow diagram generally showing oneembodiment of an overview process for elastically scaling a project;

FIG. 12 illustrates a logical flow diagram generally showing oneembodiment of a process for receiving resource allocation direction froman operator manipulating a user interface control;

FIG. 13 illustrates a logical flow diagram generally showing oneembodiment of a process for increasing a project's resources as part ofelastic scaling;

FIG. 14 depicts a logical flow diagram generally showing one embodimentof a process for responding to a requested decrease in projectresources;

FIG. 15 illustrates a logical flow diagram generally showing oneembodiment of process for queuing resource requests;

FIG. 16 depicts a logical flow diagram generally showing one embodimentof process for elastically scaling based on index storage size;

FIG. 17 depicts a logical flow diagram generally showing one embodimentof a process for elastically scaling based on indexing performance;

FIG. 18 depicts a logical flow diagram generally showing one embodimentof a process for elastically scaling based on an event time window;

FIG. 19 illustrates a logical flow diagram generally showing oneembodiment of a process for changing a number of indexers associatedwith an index store

FIG. 20 shows a logical flow diagram generally showing one embodiment ofa process to recall archived data for re-indexing;

FIG. 21 illustrates a logical flow diagram generally showing oneembodiment of a process for transitioning to scaled index stores;

FIG. 22 illustrates a logical flow diagram generally showing oneembodiment of an input proxy operation; and

FIG. 23 illustrates a non-exhaustive example of a use case of anembodiment of user-interface controls for managing and processing datavolumes.

DESCRIPTION OF VARIOUS EMBODIMENTS

Throughout the specification and claims, the following terms take themeanings explicitly associated herein, unless the context clearlydictates otherwise. The phrase “in one embodiment” as used herein doesnot necessarily refer to the same embodiment, though it may.Furthermore, the phrase “in another embodiment” as used herein does notnecessarily refer to a different embodiment, although it may. Thus, asdescribed below, various embodiments may be readily combined, withoutdeparting from the scope or spirit of the invention.

In addition, as used herein, the term “or” is an inclusive “or”operator, and is equivalent to the term “and/or,” unless the contextclearly dictates otherwise. The term “based on” is not exclusive andallows for being based on additional factors not described, unless thecontext clearly dictates otherwise. In addition, throughout thespecification, the meaning of “a,” “an,” and “the” include pluralreferences. The meaning of “in” includes “in” and “on.”

Various embodiments now will be described more fully hereinafter withreference to the accompanying drawings, which form a part hereof, andwhich show, by way of illustration, specific exemplary embodiments bywhich the invention may be practiced. The embodiments may, however, beembodied in many different forms and should not be construed as limitedto the embodiments set forth herein; rather, these embodiments areprovided so that this disclosure will be thorough and complete, and willfully convey the scope of the embodiments to those skilled in the art.Among other things, the various embodiments may be methods, systems,media or devices. Accordingly, the various embodiments may take the formof an entirely hardware embodiment, an entirely software embodiment oran embodiment combining software and hardware aspects. The followingdetailed description is, therefore, not to be taken in a limiting sense.

For example embodiments, the following terms are also used hereinaccording to the corresponding meaning, unless the context clearlydictates otherwise.

“Frontend User” as used herein may represent users at the outercloud-based edge of some of the described embodiments. This outer edgemay often be described herein as the Web Application Layer, or Cloudlayer.

“Core User” as used herein may represent abstract users that are withinthe middle of the layers of described embodiments. These middle layersmay often be described herein as Search Head layers, or Core layers.

“Apps” as used herein may collectively represent software programs andprocesses that may implement various features and processing for thevarious embodiments, some of which are described herein. Apps may giveusers insights into their projects with dashboards, reports, datainputs, and saved searches that may work in the project environment fromthe moment they are installed. Apps may include new views and dashboardsthat may completely reconfigure the way a project looks. Or, they may beas complex as an entirely new program. In some embodiments, Apps mayalso represent index resources.

“Index”, “Indexer”, “Indexing”, and “Index Storage” as used herein mayrepresent elements of described embodiments that may index and storedata and events. Indexers may collect, parse, and store data tofacilitate fast and accurate information retrieval. Index design mayincorporate interdisciplinary concepts from linguistics, cognitivepsychology, mathematics, informatics, physics, and computer science.Also, Indexes may reside in flat files in a data store on a file system.Index files may be managed to facilitate flexible searching and fastdata retrieval, eventually archiving them according to a configurableschedule. During indexing, incoming raw data may be processed to enablefast search and analysis, the results of which may be stored in anindex. As part of the indexing process, the indexer may add knowledge tothe data in various ways, including by: separating a data stream intoindividual, searchable events; creating or identifying timestamps;extracting fields such as host, source, and source type; performinguser-defined actions on the incoming data, such as identifying customfields, masking sensitive data, writing new or modified keys, applyingbreaking rules for multi-line events, filtering unwanted events, androuting events to specified indexes or servers, and the like. In someembodiments, index store may store data indexed by one or more indexers.In at least one embodiment, indexer may include indexer severs.

“Roles” as used herein may represent definitions of the accesspermissions and authorizations that enable a Core User to executevarious features, Apps, or access data, in the various embodiments.Roles may define how a Core User may interact with Apps, Indexes,Indexers, and the like.

“Dimension” as used herein when describing elastic scaling, may refer tothe particular kind of project resources that may be scaled, e.g., indexstorage, processing performance, time-window, price, network bandwidth,and the like. Embodiments may be arranged and configured to definedimensions differently, e.g., one embodiment may be arranged to definean elastic scaling dimension that represents network latency, whereanother embodiment may be arranged and configured to combine CPU quota,network latency, network bandwidth into a single dimension representingprocessing performance. One of ordinary skill in the art will appreciatethat there may be many combinations of resources that may arranged intoelastic scaling dimensions.

Multi-tenant cloud-based data storage volumes may be built to supportmanual and rule-based elastic scaling. Elastic scaling may occur in oneor more dimensions, such as scaling of storage, scaling of processingperformance, or time windows of received data, and the like. Elasticscaling may occur in one or more dimensions singly or in combination. Ifelastic scaling occurs, the appropriate objects, processes, memory, andstorage may be scaled to meet the request resource increase or decrease.There may be numerous dependent or supporting systems that may need toscale in response to an elastic scaling request. For example, a requestto elastically scale processing performance may require one or moreelements of the system to be scaled in addition to the CPU quota, suchas, disk quota, high local cache quota, and the like.

The following briefly describes embodiments in order to provide a basicunderstanding of some aspects of the invention. This brief descriptionis not intended as an extensive overview. It is not intended to identifykey or critical elements, or to delineate or otherwise narrow the scope.Its purpose is merely to present some concepts in a simplified form as aprelude to the more detailed description that is presented later.

Briefly stated, various embodiments are directed towards a system andmethod for a cloud-based front end that may abstract and enable accessto the underlying cloud-hosted elements and objects that may be part ofa multi-tenant application, such as a search application. Search objectsmay be employed to access indexed objects. Also, one or more projectscan be elastically scaled for a user to provide resources that may meetthe specific needs of each project.

In some embodiments, at least one project for at least one frontend usermay be initialized. In at least one embodiment, the frontend user may beenabled to interact with the project through at least one application.Each project may have a corresponding index store, which may include oneor more indexer servers. In at least one embodiment, a data volume limitmay be established for the index store. The data volume limit may bebased on a selection by the frontend user.

Data provided for the project may be indexed. In some embodiments, if anamount of indexed data in the index store is less than the data volumelimit, then the indexed data may be stored in the index store. In otherembodiments, if the amount of indexed data in the index store at leastequals the data volume limit, then the indexed data may be stored in anoverflow index store. In at least one embodiment, the indexed data inthe index store may be accessible to the frontend user and the indexeddata in the overflow index store may be inaccessible to the frontenduser (e.g., the frontend user may be prevented from accessing the dataunless the user increases the data volume limit, such as by purchasingadditional data storage).

If the data volume limit is increased, then at least a portion ofindexed data in the overflow index store may be provided to the indexstore, such that the provided indexed data is accessible in the indexstore to the frontend user. In at least one embodiment, the data volumelimit may be increased based on another selection by the frontend user.

In other embodiments, the user may be enabled to elastically scale oneor more computing resources associated with a project. A resourceallocation may be determined for indexing data provided for a projectfor each of a plurality of resources. In at least one embodiment, theresources may include at least one indexer server instance that indexesthe provided data, a data store (i.e., storage capacity) that stores theindexed data, an event time window, or the like.

In at least one embodiment, a request may be provided from a user toscale at least one of the plurality of resources. In some embodiments,the user may be enabled to utilize a slider control (or other userinterface) to manually adjust one or more computing resources. Inresponse to the request, the resource allocation for at least one of theplurality of resources may be adjusted based on the request. At leastone of the plurality of resources may be changed based on the adjustedresource allocation, which may be employed to subsequently index dataprovided for the project. In some embodiments, at least one type ofadditional resource may be allocated if the request indicates anincrease in the plurality of resources. In other embodiments, less of atleast one type of resource may be allocated if the change indicates adecrease in the plurality of resources.

In some embodiments, an increase or decrease in one resource maycorrespond to an increase or decrease in another resource. In at leastone embodiment, if a resource is elastically scaled, then a number ofindexers may be increased or decreased to accommodate the change inresources. In some embodiments, decreasing a number of indexers mayinclude marking an indexer as read-only and increasing a number ofindexers may include marking a read-only indexer as read/write and/oradding a new indexer.

In some embodiments, changing resources may include changing a number ofindexer servers employed to index data for the project, changing anamount of storage for the data store to store data for the project,changing an amount of memory employed to process the indexing of datafor the project, changing an amount of processors employed to processthe indexing of data for the project, or the like.

Additionally, it should be appreciated that though many embodimentsdescribed herein may be cloud-based, embodiments should not beconsidered so limited. One of ordinary skill in the art will recognizethat enabling embodiments may be arranged to be partially deployed incloud-based configurations with some elements in the cloud and someelements separate from cloud based resources. Likewise, enablingembodiments may be arranged to be deployed and operate in configurationsentirely separate from cloud-based resources.

Illustrative Operating Environment

FIG. 1 shows components of an environment in which various embodimentsmay be practiced. Not all of the components may be required to practicethe various embodiments, and variations in the arrangement and type ofthe components may be made without departing from the spirit or scope ofthe various embodiments.

In at least one embodiment, cloud network 102 enables one or morenetwork services for a user based on the operation of correspondingarrangements 104 and 106 of virtually any type of networked computingdevice. As shown, the networked computing devices may include servernetwork device 112, host network device 114, enclosure of blade servers110, enclosure of server computers 116, super computer network device118, and the like. Although not shown, one or more mobile devices may beincluded in cloud network 102 in one or more arrangements to provide oneor more network services to a user. Also, these arrangements ofnetworked computing devices may or may not be mutually exclusive of eachother.

Additionally, the user may employ a plurality of virtually any type ofwired or wireless networked computing devices to communicate with cloudnetwork 102 and access at least one of the network services enabled byone or more of arrangements 104 and 106. These networked computingdevices may include tablet mobile device 122, handheld mobile device124, wearable mobile device 126, desktop network device 120, and thelike. Although not shown, in various embodiments, the user may alsoemploy notebook computers, desktop computers, microprocessor-based orprogrammable consumer electronics, network appliances, mobiletelephones, smart telephones, pagers, radio frequency (RF) devices,infrared (IR) devices, Personal Digital Assistants (PDAs), televisions,integrated devices combining at least one of the preceding devices, andthe like.

One embodiment of a mobile device is described in more detail below inconjunction with FIG. 3. Generally, mobile devices may include virtuallyany substantially portable networked computing device capable ofcommunicating over a wired, wireless, or some combination of wired andwireless network.

In various embodiments, network 102 may employ virtually any form ofcommunication technology and topology. For example, network 102 caninclude local area networks Personal Area Networks (PANs), (LANs),Campus Area Networks (CANs), Metropolitan Area Networks (MANs) Wide AreaNetworks (WANs), direct communication connections, and the like, or anycombination thereof. On an interconnected set of LANs, including thosebased on differing architectures and protocols, a router acts as a linkbetween LANs, enabling messages to be sent from one to another. Inaddition, communication links within networks may include virtually anytype of link, e.g., twisted wire pair lines, optical fibers, open airlasers or coaxial cable, plain old telephone service (POTS), waveguides, acoustic, full or fractional dedicated digital communicationlines including T1, T2, T3, and T4, and/or other carrier and other wiredmedia and wireless media. These carrier mechanisms may includeE-carriers, Integrated Services Digital Networks (ISDNs), universalserial bus (USB) ports, Firewire ports, Thunderbolt ports, DigitalSubscriber Lines (DSLs), wireless links including satellite links, orother communications links known to those skilled in the art. Moreover,these communication links may further employ any of a variety of digitalsignaling technologies, including without limit, for example, DS-0,DS-1, DS-2, DS-3, DS-4, OC-3, OC-12, OC-48, or the like. Furthermore,remotely located computing devices could be remotely connected tonetworks via a modem and a temporary communication link. In essence,network 102 may include virtually any communication technology by whichinformation may travel between computing devices. Additionally, in thevarious embodiments, the communicated information may include virtuallyany kind of information including, but not limited to processor-readableinstructions, data structures, program modules, applications, raw data,control data, archived data, video data, voice data, image data, textdata, and the like.

Network 102 may be partially or entirely embodied by one or morewireless networks. A wireless network may include any of a variety ofwireless sub-networks that may further overlay stand-alone ad-hocnetworks, and the like. Such sub-networks may include mesh networks,Wireless LAN (WLAN) networks, Wireless Router (WR) mesh, cellularnetworks, pico networks, PANs, Open Air Laser networks, Microwavenetworks, and the like. Network 102 may further include an autonomoussystem of intermediate network devices such as terminals, gateways,routers, switches, firewalls, load balancers, and the like, which arecoupled to wired and/or wireless communication links. These autonomousdevices may be operable to move freely and randomly and organizethemselves arbitrarily, such that the topology of network 102 may changerapidly.

Network 102 may further employ a plurality of wired and wireless accesstechnologies, e.g., 2nd (2G), 3rd (3G), 4th (4G), 5^(th) (5G) generationwireless access technologies, and the like, for mobile devices. Thesewired and wireless access technologies may also include Global Systemfor Mobile communication (GSM), General Packet Radio Services (GPRS),Enhanced Data GSM Environment (EDGE), Code Division Multiple Access(CDMA), Wideband Code Division Multiple Access (WCDMA), Long TermEvolution Advanced (LTE), Universal Mobile Telecommunications System(UMTS), Orthogonal frequency-division multiplexing (OFDM), Wideband CodeDivision Multiple Access (W-CDMA), Code Division Multiple Access 2000(CDMA2000), Evolution-Data Optimized (EV-DO), High-Speed Downlink PacketAccess (HSDPA), IEEE 802.16 Worldwide Interoperability for MicrowaveAccess (WiMax), ultra wide band (UWB), user datagram protocol (UDP),transmission control protocol/Internet protocol (TCP/IP), any portion ofthe Open Systems Interconnection (OSI) model protocols, Short MessageService (SMS), Multimedia Messaging Service (MMS), Web Access Protocol(WAP), Session Initiation Protocol/Real-time Transport Protocol(SIP/RTP), or any of a variety of other wireless or wired communicationprotocols. In one non-limiting example, network 102 may enable a mobiledevice to wirelessly access a network service through a combination ofseveral radio network access technologies such as GSM, EDGE, SMS, HSDPA,and the like.

Enclosure of Blade Servers

FIG. 2A shows one embodiment of an enclosure of blade servers 200, whichare also illustrated in FIG. 1. Enclosure of blade servers 200 mayinclude many more or fewer components than those shown in FIG. 2A.However, the components shown are sufficient to disclose an illustrativeembodiment. Generally, a blade server is a stripped down servercomputing device with a modular design optimized to minimize the use ofphysical space and energy. A blade enclosure can include several bladeservers and provide each with power, cooling, network interfaces,input/output interfaces, and resource management. Although not shown, anenclosure of server computers typically includes several computers thatmerely require a network connection and a power cord connection tooperate. Each server computer often includes redundant components forpower and interfaces.

As shown in the figure, enclosure 200 contains power supply 204, andinput/output interface 206, rack logic 208, several blade servers 210,212, 214, and 216, and backplane 202. Power supply 204 provides power toeach component and blade server within the enclosure. The input/outputinterface 206 provides internal and external communication forcomponents and blade servers within the enclosure. Backplane 208 canenable passive and active communication of power, logic, input signals,and output signals for each blade server.

Illustrative Blade Server

FIG. 2B illustrates an illustrative embodiment of blade server 250,which may include many more or fewer components than those shown. Asshown in FIG. 2A, a plurality of blade servers may be included in oneenclosure that shares resources provided by the enclosure to reducesize, power, and cost.

Blade server 250 includes processor 252 which communicates with memory256 via bus 254. Blade server 250 also includes input/output interface290, processor-readable stationary storage device 292, andprocessor-readable removable storage device 294. Input/output interface290 can enable blade server 250 to communicate with other blade servers,mobile devices, network devices, and the like. Interface 190 may providewireless and/or wired communication links for blade server.Processor-readable stationary storage device 292 may include devicessuch as an electromagnetic storage device (hard disk), solid state harddisk (SSD), hybrid of both an SSD and a hard disk, and the like. Also,processor-readable removable storage device 294 enables processor 252 toread non-transitive storage media for storing and accessingprocessor-readable instructions, modules, data structures, and otherforms of data. The non-transitive storage media may include Flashdrives, tape media, floppy media, and the like.

Memory 256 may include Random Access Memory (RAM), Read-Only Memory(ROM), hybrid of RAM and ROM, and the like. As shown, memory 256includes operating system 258 and basic input/output system (BIOS) 260for enabling the operation of blade server 250. In various embodiments,a general-purpose operating system may be employed such as a version ofUNIX, or LINUX™, or a specialized server operating system such asMicrosoft's Windows Server™ and Apple Computer's IoS Server™.

Memory 256 further includes one or more data storage 270, which can beutilized by blade server 250 to store, among other things, applications280 and/or other data. Data stores 270 may include program code, data,algorithms, and the like, for use by processor 252 to execute andperform actions. In one embodiment, at least some of data store 270might also be stored on another component of blade server 250,including, but not limited to, processor-readable removable storagedevice 294, processor-readable stationary storage device 292, or anyother processor-readable storage device (not shown). Data storage 270may include, for example, raw data 272, and indexed data 274.

Applications 280 may include processor executable instructions which,when executed by blade server 250, transmit, receive, and/or otherwiseprocess messages, audio, video, and enable communication with othernetworked computing devices. Examples of application programs includedatabase servers, file servers, calendars, transcoders, and so forth.Applications 280 may include, for example, cloud search application 282,and indexing application 284.

Human interface components (not pictured), may be remotely associatedwith blade server 250, which can enable remote input to and/or outputfrom blade server 250. For example, information to a display or from akeyboard can be routed through the input/output interface 290 toappropriate peripheral human interface components that are remotelylocated. Examples of peripheral human interface components include, butare not limited to, an audio interface, a display, keypad, pointingdevice, touch interface, and the like.

Illustrative Mobile Device

FIG. 3 shows one embodiment of mobile device 300 that may include manymore or less components than those shown. Mobile device 300 mayrepresent, for example, at least one embodiment of mobile devices shownin FIG. 1.

Mobile device 300 includes processor 302 in communication with memory304 via bus 328. Mobile device 300 also includes power supply 330,network interface 332, audio interface 356, display 350, keypad 352,illuminator 354, video interface 342, input/output interface 338, hapticinterface 364, global positioning systems (GPS) receiver 358, Open airgesture interface 360, temperature interface 362, camera(s) 340,projector 346, pointing device interface 366, processor-readablestationary storage device 334, and processor-readable removable storagedevice 336. Power supply 330 provides power to mobile device 300. Arechargeable or non-rechargeable battery may be used to provide power.The power may also be provided by an external power source, such as anAC adapter or a powered docking cradle that supplements and/or rechargesthe battery. And in one embodiment, although not shown, a gyroscope maybe employed within mobile device 300 to measuring and/or maintaining anorientation of mobile device 300.

Mobile device 300 may optionally communicate with a base station (notshown), or directly with another computing device. Network interface 332includes circuitry for coupling mobile device 300 to one or morenetworks, and is constructed for use with one or more communicationprotocols and technologies including, but not limited to, protocols andtechnologies that implement any portion of the Open SystemsInterconnection (OSI) model for mobile communication (GSM), codedivision multiple access (CDMA), time division multiple access (TDMA),user datagram protocol (UDP), transmission control protocol/Internetprotocol (TCP/IP), Short Message Service (SMS), Multimedia MessagingService (MMS), general packet radio service (GPRS), WAP, ultra wide band(UWB), IEEE 802.16 Worldwide Interoperability for Microwave Access(WiMax), Session Initiation Protocol/Real-time Transport Protocol(SIP/RTP), or any of a variety of other wireless communicationprotocols. Network interface 332 is sometimes known as a transceiver,transceiving device, or network interface card (NIC).

Audio interface 356 is arranged to produce and receive audio signalssuch as the sound of a human voice. For example, audio interface 356 maybe coupled to a speaker and microphone (not shown) to enabletelecommunication with others and/or generate an audio acknowledgementfor some action. A microphone in audio interface 356 can also be usedfor input to or control of mobile device 300, e.g., using voicerecognition, detecting touch based on sound, and the like.

Display 350 may be a liquid crystal display (LCD), gas plasma,electronic ink, light emitting diode (LED), Organic LED (OLED) or anyother type of light reflective or light transmissive display that can beused with a computing device. Display 350 may also include a touchinterface 344 arranged to receive input from an object such as a stylusor a digit from a human hand, and may use resistive, capacitive, surfaceacoustic wave (SAW), infrared, radar, or other technologies to sensetouch and/or gestures. Projector 346 may be a remote handheld projectoror an integrated projector that is capable of projecting an image on aremote wall or any other reflective object such as a remote screen.

Video interface 342 may be arranged to capture video images, such as astill photo, a video segment, an infrared video, or the like. Forexample, video interface 342 may be coupled to a digital video camera, aweb-camera, or the like. Video interface 342 may comprise a lens, animage sensor, and other electronics. Image sensors may include acomplementary metal-oxide-semiconductor (CMOS) integrated circuit,charge-coupled device (CCD), or any other integrated circuit for sensinglight.

Keypad 352 may comprise any input device arranged to receive input froma user. For example, keypad 352 may include a push button numeric dial,or a keyboard. Keypad 352 may also include command buttons that areassociated with selecting and sending images. Illuminator 354 mayprovide a status indication and/or provide light. Illuminator 354 mayremain active for specific periods of time or in response to events. Forexample, when illuminator 354 is active, it may backlight the buttons onkeypad 352 and stay on while the mobile device is powered. Also,illuminator 354 may backlight these buttons in various patterns whenparticular actions are performed, such as dialing another mobile device.Illuminator 354 may also cause light sources positioned within atransparent or translucent case of the mobile device to illuminate inresponse to actions.

Mobile device 300 also comprises input/output interface 338 forcommunicating with external peripheral devices or other computingdevices such as other mobile devices and network devices. The peripheraldevices may include an audio headset, display screen glasses, remotespeaker system, remote speaker and microphone system, and the like.Input/output interface 338 can utilize one or more technologies, such asUniversal Serial Bus (USB), Infrared, WiFi, WiMax, Bluetooth™, and thelike. Haptic interface 364 is arranged to provide tactile feedback to auser of the mobile device. For example, the haptic interface 364 may beemployed to vibrate mobile device 300 in a particular way when anotheruser of a computing device is calling. Temperature interface 362 may beused to provide a temperature measurement input and/or a temperaturechanging output to a user of mobile device 300. Open air gestureinterface 360 may sense physical gestures of a user of mobile device300, for example, by using single or stereo video cameras, radar, agyroscopic sensor inside a device held or worn by the user, or the like.Camera 340 may be used to track physical eye movements of a user ofmobile device 300.

GPS transceiver 358 can determine the physical coordinates of mobiledevice 300 on the surface of the Earth, which typically outputs alocation as latitude and longitude values. GPS transceiver 358 can alsoemploy other geo-positioning mechanisms, including, but not limited to,triangulation, assisted GPS (AGPS), Enhanced Observed Time Difference(E-OTD), Cell Identifier (CI), Service Area Identifier (SAI), EnhancedTiming Advance (ETA), Base Station Subsystem (BSS), or the like, tofurther determine the physical location of mobile device 300 on thesurface of the Earth. It is understood that under different conditions,GPS transceiver 358 can determine a physical location for mobile device300. In at least one embodiment, however, mobile device 300 may, throughother components, provide other information that may be employed todetermine a physical location of the device, including for example, aMedia Access Control (MAC) address, IP address, and the like.

Human interface components can be peripheral devices that are physicallyseparate from mobile device 300, allowing for remote input and/or outputto mobile device 300. For example, information routed as described herethrough human interface components such as display 350 or keyboard 352can instead be routed through network interface 332 to appropriate humaninterface components located remotely. Examples of human interfaceperipheral components that may be remote include, but are not limitedto, audio devices, pointing devices, keypads, displays, cameras,projectors, and the like. These peripheral components may communicateover a Pico Network such as Bluetooth™, Zigbee™ and the like. Onenon-limiting example of a mobile device with such peripheral humaninterface components is a wearable computing device, which might includea remote pico projector along with one or more cameras that remotelycommunicate with a separately located mobile device to sense a user'sgestures toward portions of an image projected by the pico projectoronto a reflected surface such as a wall or the user's hand.

A mobile device may include a browser application that is configured toreceive and to send web pages, web-based messages, graphics, text,multimedia, and the like. The mobile device's browser application mayemploy virtually any programming language, including a wirelessapplication protocol messages (WAP), and the like. In at least oneembodiment, the browser application is enabled to employ Handheld DeviceMarkup Language (HDML), Wireless Markup Language (WML), WMLScript,JavaScript, Standard Generalized Markup Language (SGML), HyperTextMarkup Language (HTML), eXtensible Markup Language (XML), HTML5, and thelike.

Memory 304 may include Random Access Memory (RAM), Read-Only Memory(ROM), and/or other types of memory. Memory 304 illustrates an exampleof computer-readable storage media (devices) for storage of informationsuch as computer-readable instructions, data structures, program modulesor other data. Memory 304 stores a basic input/output system (BIOS) 308for controlling low-level operation of mobile device 300. The memoryalso stores an operating system 306 for controlling the operation ofmobile device 300. It will be appreciated that this component mayinclude a general-purpose operating system such as a version of UNIX, orLINUX™, or a specialized mobile computer communication operating systemsuch as Windows Mobile™, or the Symbian® operating system. The operatingsystem may include, or interface with a Java virtual machine module thatenables control of hardware components and/or operating systemoperations via Java application programs.

Memory 304 further includes one or more data storage 310, which can beutilized by mobile device 300 to store, among other things, applications320 and/or other data. For example, data storage 310 may also beemployed to store information that describes various capabilities ofmobile device 300. The information may then be provided to anotherdevice based on any of a variety of events, including being sent as partof a header during a communication, sent upon request, or the like. Datastorage 310 may also be employed to store social networking informationincluding address books, buddy lists, aliases, user profile information,or the like. Data storage 310 may further include program code, data,algorithms, and the like, for use by a processor, such as processor 302to execute and perform actions. In one embodiment, at least some of datastorage 310 might also be stored on another component of mobile device300, including, but not limited to, non-transitory processor-readableremovable storage device 336, processor-readable stationary storagedevice 334, or even external to the mobile device. Data storage 310 mayinclude, for example, raw data 312, and index data 314.

Applications 320 may include computer executable instructions which,when executed by mobile device 300, transmit, receive, and/or otherwiseprocess instructions and data. Applications 320 may include, forexample, Cloud Search application 322, and Indexing Application 324.Other examples of application programs include calendars, searchprograms, email client applications, IM applications, SMS applications,Voice Over Internet Protocol (VOIP) applications, contact managers, taskmanagers, transcoders, database programs, word processing programs,security applications, spreadsheet programs, games, search programs, andso forth.

Illustrative Network Device

FIG. 4 shows one embodiment of network device 400 that may be includedin a system implementing the invention. Network device 400 may includemany more or less components than those shown in FIG. 4. However, thecomponents shown are sufficient to disclose an illustrative embodimentfor practicing the present invention. Network device 400 may represent,for example, one embodiment of at least one of network device 112, 114,or 120 of FIG. 1.

As shown in the figure, network device 400 includes a processor 402 incommunication with a memory 404 via a bus 428. Network device 400 alsoincludes a power supply 430, network interface 432, audio interface 456,display 450, keyboard 452, input/output interface 438,processor-readable stationary storage device 434, and processor-readableremovable storage device 436. Power supply 430 provides power to networkdevice 400.

Network interface 432 includes circuitry for coupling network device 400to one or more networks, and is constructed for use with one or morecommunication protocols and technologies including, but not limited to,protocols and technologies that implement any portion of the OpenSystems Interconnection model (OSI model), global system for mobilecommunication (GSM), code division multiple access (CDMA), time divisionmultiple access (TDMA), user datagram protocol (UDP), transmissioncontrol protocol/Internet protocol (TCP/IP), Short Message Service(SMS), Multimedia Messaging Service (MMS), general packet radio service(GPRS), WAP, ultra wide band (UWB), IEEE 802.16 WorldwideInteroperability for Microwave Access (WiMax), Session InitiationProtocol/Real-time Transport Protocol (SIP/RTP), or any of a variety ofother wired and wireless communication protocols. Network interface 432is sometimes known as a transceiver, transceiving device, or networkinterface card (NIC). Network device 400 may optionally communicate witha base station (not shown), or directly with another computing device.

Audio interface 456 is arranged to produce and receive audio signalssuch as the sound of a human voice. For example, audio interface 456 maybe coupled to a speaker and microphone (not shown) to enabletelecommunication with others and/or generate an audio acknowledgementfor some action. A microphone in audio interface 456 can also be usedfor input to or control of network device 400, for example, using voicerecognition.

Display 450 may be a liquid crystal display (LCD), gas plasma,electronic ink, light emitting diode (LED), Organic LED (OLED) or anyother type of light reflective or light transmissive display that can beused with a computing device. Display 450 may be a handheld projector orpico projector capable of projecting an image on a wall or other object.

Network device 400 also may also comprise input/output interface 438 forcommunicating with external devices not shown in FIG. 4. Input/outputinterface 438 can utilize one or more wired or wireless communicationtechnologies, such as USB™, Firewire™, WiFi, WiMax, Thunderbolt™,Infrared, Bluetooth™, Zigbee™, serial port, parallel port, and the like.

Human interface components can be physically separate from networkdevice 400, allowing for remote input and/or output to network device400. For example, information routed as described here through humaninterface components such as display 450 or keyboard 452 can instead berouted through the network interface 432 to appropriate human interfacecomponents located elsewhere on the network. Human interface componentsinclude any component that allows the computer to take input from, orsend output to, a human user of a computer.

Memory 404 may include Random Access Memory (RAM), Read-Only Memory(ROM), and/or other types of memory. Memory 404 illustrates an exampleof computer-readable storage media (devices) for storage of informationsuch as computer-readable instructions, data structures, program modulesor other data. Memory 404 stores a basic input/output system (BIOS) 408for controlling low-level operation of network device 400. The memoryalso stores an operating system 406 for controlling the operation ofnetwork device 400. It will be appreciated that this component mayinclude a general-purpose operating system such as a version of UNIX, orLINUX™, or a specialized operating system such as MicrosoftCorporation's Windows® operating system, or the Apple Corporation's iOS®operating system. The operating system may include, or interface with aJava virtual machine module that enables control of hardware componentsand/or operating system operations via Java application programs.

Memory 404 further includes one or more data storage 410, which can beutilized by network device 400 to store, among other things,applications 420 and/or other data. For example, data storage 410 mayalso be employed to store information that describes variouscapabilities of network device 400. The information may then be providedto another device based on any of a variety of events, including beingsent as part of a header during a communication, sent upon request, orthe like. Data storage 410 may also be employed to store socialnetworking information including address books, buddy lists, aliases,user profile information, or the like. Data stores 410 may furtherinclude program code, data, algorithms, and the like, for use by aprocessor, such as processor 402 to execute and perform actions. In oneembodiment, at least some of data store 410 might also be stored onanother component of network device 400, including, but not limited to,non-transitory media inside processor-readable removable storage device436, processor-readable stationary storage device 434, or any othercomputer-readable storage device within network device 400, or evenexternal to network device 400. Data storage 410 may include, forexample, raw data 412, and indexed data 414.

Applications 420 may include computer executable instructions which,when executed by network device 400, transmit, receive, and/or otherwiseprocess messages (e.g., SMS, Multimedia Messaging Service (MMS), InstantMessage (IM), email, and/or other messages), audio, video, and enabletelecommunication with another user of another mobile device. Otherexamples of application programs include calendars, search programs,email client applications, IM applications, SMS applications, Voice OverInternet Protocol (VOIP) applications, contact managers, task managers,transcoders, database programs, word processing programs, securityapplications, spreadsheet programs, games, search programs, and soforth. Applications 420 may include, for example, cloud searchapplication 422, and indexing application 424.

Illustrative System Diagram

FIG. 5 depicts an embodiment where the top layer of the figure,indicated as Web Application Layer 502, may represent a cloud-basedfront end that may abstract and enable access to the underlyingcloud-hosted elements and objects that may be part of a multi-tenantapplication that may comprise Core User (e.g., Core User 518 and CoreUser 520), Roles (e.g., Role 522 and Role 524), and Apps (e.g., App 526and App 528), indicated as the Search Head 504. The objects in theSearch Head 504 layer may be employed to access the Index objectslocated in the Indexers 506 layer of FIG. 5. The two projects, Project 1(i.e., project 508) and Project 2 (i.e., project 510) in the WebApplication Layer 502 may be examples of projects that have beenelastically scaled to provide resources that may meet the specific needsof each project. As depicted, Project 1 may require twice as muchperformance and Project 2, the figure represents this with theadditional Apps (i.e., App 526 and App 528) in the Search Head 504layer, and the two index stores (i.e., index 530 and index 532) in theIndexer 506 layer.

Also, the embodiment in FIG. 5, demonstrates that a Frontend User mayhave access to one or more Projects. For example, frontend user 512 mayhave access to project 508, Frontend User 516 may have access to project510, and Frontend User 514 may have access to both project 508 andproject 510. An embodiment may enable the Search Head 504 layer of aProject (e.g., project 508) to create unique Core Users in the SearchHead 504 layer that may be linked to Frontend Users from the WebApplication Layer 502. For example, Core User 518 may be linked toFrontend User 512 and Core User 520 may be linked to Frontend User 514.

A Role of the Core User that may be linked to the Frontend User mayenable access control for the Apps and other objects within the SearchHead layer. For example, Role 522 of Core User 518 may enable FrontendUser 512 to access control for App 526 and App 528. Similarly, Role 524of Core User 520 may enable Frontend User 514 to access control for App526 and App 528. The Role may determine the specific features that aremade available to a Core User, and a Frontend User may have its accesswithin a Project controlled by the Role of the Core User it is linkedwith. In other words, as depicted by FIG. 5, the Roles may be thought ofas providing pathways for the Frontend User to reach the Apps. In someembodiments, the Roles may also control access to indexers. For example,Role 522 may control access of Core User 518 to Apps 526 and/or 528 aswell as index 530 and/or 532.

FIG. 6, depicts an embodiment where Frontend User 1 (i.e., Frontend User612) may be the owner of two projects, Project 1 (i.e., Project 608) andProject 2 (i.e., Project 610). As shown in the figure, Frontend User 2(i.e., Frontend User 614) may not be an owner of a project. But,Frontend User 2 illustrates how a Frontend User may be invited by aproject owner, represented in this embodiment by the depicted FrontendUser 1. In at least one embodiment, Frontend User 612 and/or FrontendUser 614 may be an embodiment of a Frontend User from FIG. 5. In someembodiments, Project 608 and Project 610 may be embodiments of Project508 and Project 510 of FIG. 5, respectively. Web Application Layer 602,Search Head 604, and Indexers 606 may be embodiments of Web ApplicationLayer 502, Search Head 504, and Indexers 506 of FIG. 5, respectively.

Similar to the embodiment depicted in FIG. 5, this embodiment may enableunique Core Users to be created and linked to Frontend Users. Forexample, Core User 618 and Core User 620 may be linked to Frontend User612 and Core User 622 may be linked to Frontend User 614. For eachunique Core User, a Role may be created to define the features that maybe accessed by the Frontend User. For example, Role 624 of Core User 618may define the features that may be accessed by Frontend User 612 (e.g.,App 626).

The embodiment depicted in FIG. 6, may also enable Indexes (e.g., Index632), Ports (e.g., Port 634), and associated storage to be locatedseparately from the Search Head/Core layer objects. Also, embodimentsmay locate Indexes, and Ports across more than one computing devicee.g., computing device 628 and computing device 630), including, networkcomputing devices, blade servers, individual blade computers,cloud-based compute instances, virtual machines, and the like. Further,Indexes that may be associated with different Projects may be co-locatedon the same computing device, such as, network computing devices, bladeservers, individual blade computers, cloud-based compute instances,virtual machines, and the like.

General Operation of Data Volume Management

The operation of certain aspects of the invention will now be describedwith respect to FIGS. 7-10. FIG. 7 illustrates a logical flow diagramgenerally showing one embodiment of an overview process for initiating aproject that employs embodiments of the system diagrams shown in FIGS. 5and/or 6. In some embodiments, process 700 of FIG. 7 may be implementedby and/or executed on a single network device, such as network device400 of FIG. 4. In other embodiments, process 700 or portions of process700 of FIG. 7 may be implemented by and/or executed on a plurality ofnetwork devices, such as network device 400 of FIG. 4. In yet otherembodiments, process 700 or portions of process 700 of FIG. 7 may beimplemented by and/or executed on one or more blade servers, such asblade server 250 of FIG. 2B.

Process 700 begins, after a start block, at block 702 where at least oneproject may be initialized for at least one Frontend User. In someembodiments, Roles, Apps, Indexes, or the like may be created and/orconfigured for each unique project. In some embodiments, blocks 704,706, 708, 710, and 712 may be performed in an order other thanillustrated in FIG. 7.

Processing continues at block 704, where one or more Apps may be createdand/or associated with the project. In some embodiments, the associatedApps may be identified by the Frontend User.

Process 700 continues at block 706, where at least one Role may bedetermined for the project. In some embodiments, an operator and/or theFrontend User may generate and/or modify the access permissionsassociated with the Role. In at least one embodiment, at least one Rolefor each frontend user may be determined that may establish permissionsfor interacting with the at least one project and the at least oneapplication for each Frontend User. In at least one embodiment, theRoles may configure access control for a Frontend User to the Appsand/or the indexers. For example, in some embodiments, Roles may enableone Frontend User to access one App (and/or indexer), but not anotherApp (and/or indexer). In some embodiments, a plurality of Roles may bedetermined for each Core User.

Process 700 proceeds to block 708, where a Core User on the project maybe created for the Frontend User. In at least one embodiment, creating aCore User may include determining a Core User that corresponds to afrontend user and a project, wherein the Core User enables the FrontendUser to interact with the project. In some embodiments, the Core Usermay inherit one or more corresponding Roles determined at block 706.

Process 700 continues next at block 710, where the Frontend User may belinked with the Core User and the Role.

Process 700 proceeds to block 712, where an available index store may beestablished for the project. In at least one embodiment, an availableindex store may refer to an index store that is accessible by theFrontend User. In some embodiments, the Frontend User may be enabled tosearch the available index store. In at least one embodiment, theavailable index store may include one or more indexer instances. In someembodiments, the indexers may be configured based on the Roles. Asdescribed above, access to the index store (and/or the Apps) may becontrolled by the Roles. In some other embodiments, a port may beassigned to each individual index.

Continuing to block 714, the index store may be dynamically scaled,which is described in more detail below in conjunction with FIG. 8.Briefly, however, the index store may be dynamically scaled based on theFrontend User account. For example, if the index store exceeds apre-purchased data volume, then incoming data may continue to be index,but the Frontend User may not be able to access the incoming data untilthe Frontend User pays for an increase in the data volume.

In some embodiments, the Frontend User may be enabled to select whenand/or how dynamic scaling may be employed. For example, in someembodiments, the Frontend User may determine that if an index size limitis reached, at least one of the following may occur, including:automatically deleting additional data provided for the project beyondthe size limit, the indexers may automatically stop indexing data,automatically increasing the storage size of data supported for aproject, or the like.

After block 714, process 700 may return control to a calling process.

FIG. 8 illustrates a logical flow diagram generally showing oneembodiment of a process for enabling access to a determined volume ofdata and restricting access to incoming data that exceeds the determinedvolume. In some embodiments, process 800 of FIG. 8 may be implemented byand/or executed on a single network device, such as network device 400of FIG. 4. In other embodiments, process 800 or portions of process 800of FIG. 8 may be implemented by and/or executed on a plurality ofnetwork devices, such as network device 400 of FIG. 4. In yet otherembodiments, process 800 or portions of process 800 of FIG. 8 may beimplemented by and/or executed on one or more blade servers, such asblade server 250 of FIG. 2B.

Process 800 begins, after a start block, at block 802, data may beprovided. In some embodiments, the data may be incoming data for a givenproject. In other embodiments, the data may be archived data for a givenproject that may be recovered.

Process 800 continues at block 804, where the data may be indexed.

Process 800 proceeds to decision block 806, where a determination may bemade whether a data volume limit is exceeded by the indexed data. In oneembodiment, each project may include a data volume limit. In anotherembodiment, each frontend user (or group of frontend users) may beassociated with a data volume limit. In at least one embodiment, thetotal stored data plus the indexed data may be compared to a maximumallowable data volume limit. In some embodiment, the data volume limitmay be based on an amount of storage space purchased by a user (e.g., aFrontend User). If the data volume limit is exceeded, then process 800may flow to block 810; otherwise, process 800 may flow to block 808.

At block 808, the indexed data may be stored in an available indexstore. In some embodiments, an available index store may refer to anindex store that is accessible to the user. Process 800 may proceed toblock 818.

If, at decision block 806, the data volume limit is exceeded, thenprocess 800 may flow from decision block 806 to block 810. At block 810,the indexed data may be stored in an overflow index store. In someembodiments, the overflow index store may be unavailable to the user.The overflow index store allows continued indexing of a user's data evenif the amount of data has exceeded a purchased maximum data volume.However, the user may not have access to the data in the overflow indexstore, unless the user purchases additional data volume.

In at least one embodiment, the overflow index store may be a FIFObuffer. The data in the overflow index store may remain in the overflowindex store until a user purchases additional data volume and/or thedata is removed (e.g., deleted/archived) after a predetermined amount oftime. Some embodiments for removing data from the overflow index storeare described in more detail below in conjunction with FIG. 9.

In any event, process 800 next flows to decision block 812, where adetermination may be made whether access to data in the overflow indexstore is enabled. In some embodiments, access may be enabled if the userincreases the data storage volume, such as by purchasing additional datastorage. In at least one embodiment, the data storage volume may beelastically scaled as described in more detail below in conjunction withFIGS. 11-23. If access to the overflow index store is enabled, process800 may flow to block 814; otherwise, process 800 may flow to block 818.

At block 814, an amount of data in the overflow index store to makeavailable may be determined. In some embodiments, the amount of data maybe equal to or less than an increase in data storage volume. Forexample, if the user purchases an extra 2 GB of data storage, then itmay be determined that up to 2 GB of data from the overflow index storemay be made available. In some embodiments, the determined amount ofdata may be pulled from the overflow index store based on a FIFO (firstin first out) buffer architecture of the overflow index store. In someembodiment, the indexed data that exceeds the data volume limit of theavailable index store is automatically deleted based on at least one ofa first in first out operation of the overflow index store or anyindexed data that exceeds the data volume limit.

Process 800 proceeds to block 816, where the determined amount of datamay be provided to the available index store. In at least oneembodiment, determining an amount of indexed data to copy from theoverflow index store to the index store based on at least an increase tothe data volume limit. In another embodiment, providing the data fromthe overflow index store to the available index store may includemodifying an index store flag; copying the data from the overflow indexstore to the available index store, or the like. In some embodiments, atleast a portion of the indexed data in the overflow index store may becopied to archival storage. For example, the indexed data provided fromthe overflow index store to the available index store may also beprovided to and/or copied to archival storage.

Process 800 continues next at block 818, where the user may be enabledto access the available index store. In at least one embodiment, theuser may be enabled to perform searches for data in the available indexstore.

After block 800, process 800 may return control to a calling process.

FIG. 9 illustrates a logical flow diagram generally showing oneembodiment of a process for managing an overflow index store. In someembodiments, process 900 of FIG. 9 may be implemented by and/or executedon a single network device, such as network device 400 of FIG. 4. Inother embodiments, process 900 or portions of process 900 of FIG. 9 maybe implemented by and/or executed on a plurality of network devices,such as network device 400 of FIG. 4. In yet other embodiments, process900 or portions of process 900 of FIG. 9 may be implemented by and/orexecuted on one or more blade servers, such as blade server 250 of FIG.2B.

Process 900 begins, after a start block, at decision block 902, where adetermination may be made whether to remove data from the overflow indexstore. In some embodiments, data may be removed from the overflow indexstore when it is moved to the available index store. In otherembodiments, data may be removed from the overflow index store after apredetermined amount of time. In yet other embodiments, data may beremoved from the overflow index store if the amount of data in overflowindex store exceeds a maximum overflow index store volume. If data isremoved from the overflow index store, then process 900 may flow todecision block 904; otherwise, process 900 may return control to acalling process.

At decision block 904, a determination may be made whether the removeddata is moved to archival storage. In some embodiments, thisdetermination may be based on user preferences, settings, rules (e.g.,Roles), or the like. For example, an account for the user may indicatethat the data removed from the overflow index store may be deletedwithout archiving the data. In other embodiments, the determination maybe based on whether the data was added to the available index store atblock 816 of FIG. 8. In one such embodiment, if the data was added tothe available index store, then the data may be moved to archivalstorage. If the data is moved to archival storage, then process 900 mayflow to block 906; otherwise, process 900 may flow to block 908.

At block 906, data may be moved from the overflow index store toarchival storage. In one embodiment, data may be moved to the archivalstorage based on a FIFO buffer architecture of the overflow index store.In some embodiments, an amount of data to be moved to the archivalstorage may be based on the FIFO buffer. In other embodiments, theamount of data to be moved may be based on an amount of data added tothe available index store at block 816 of FIG. 8.

Process 900 proceeds to block 908, where data may be deleted from theoverflow index store. In one embodiment, data may be deleted based on aFIFO buffer architecture of the overflow index store. In someembodiments, an amount of data to be deleted may be based on the FIFObuffer. In other embodiments, the amount of data to be deleted may bebased on an amount of data added to the available index store at block816 of FIG. 8.

After block 908, process 900 may return control to a calling process.

FIG. 10, illustrates a logical flow diagram generally showing oneembodiment of a process for enabling a project owner to invite anotheruser into the project. In some embodiments, process 1000 of FIG. 10 maybe implemented by and/or executed on a single network device, such asnetwork device 400 of FIG. 4. In other embodiments, process 1000 orportions of process 1000 of FIG. 10 may be implemented by and/orexecuted on a plurality of network devices, such as network device 400of FIG. 4. In yet other embodiments, process 1000 or portions of process1000 of FIG. 10 may be implemented by and/or executed on one or moreblade servers, such as blade server 250 of FIG. 2B.

Process 1000 begins, after a start block, at block 1002, where a projectowner may be enabled to send an invitation to an invited user. Also, anyproject user, or administrative user having the authority to inviteusers to a particular project may send invitations. Further, though notdepicted in FIG. 10, administrators, or other authorized users maydefine negative or positive restrictions on the users that may beinvited to project. Restrictions may be defined for many purposesincluding, project security, privacy, licensing, and the like.Restrictions may be based on individual users as well as groups, lists,patterns, and the like.

Process 1000 proceeds to decision block 1004, where a determination maybe made whether a user accepted the invitation. In at least oneembodiment, an invited user may have the choice to accept theinvitation. However, some embodiments may automatically join invitedusers to a project without giving them the option to decline theinvitation. If an invited user declines or ignores an invitation, thenprocess 1000 may return to the calling process; otherwise, process 1000may flow to decision block 1006. In some embodiments the sender of theinvitation may receive notice that the invitation has been declined orignored.

At decision block 1006, a determination may be made whether the inviteduser has a Frontend User account. If the invited user has an activeFrontend User account, then process 1000 may flow to block 1010;otherwise, process 1000 may flow to block 1008.

At block 1008, the invited user may create a Frontend User account.

Processing continues at block 1010, where a new Core User on a projectmay be creased. Proceeding to block 1012, a corresponding new Role forthe new Core User may also be determined. In some embodiments, one ormore new Roles may be created for the new Core User. In otherembodiments, the new Core User may inherit one or more Roles from theuser who initiated in invitation.

Process 1000 proceeds to block 1014, where the invited Frontend User maybe linked with the new Core User and the new Role. After block 1014,process 1000 may return control to a calling process.

General Operation of Elastic Scaling of Data Volumes

The operation of certain aspects of the invention will now be describedwith respect to FIGS. 11-22. FIG. 11 illustrates a logical flow diagramgenerally showing one embodiment of an overview process for elasticallyscaling a project. In some embodiments, process 1100 of FIG. 11 may beimplemented by and/or executed on a single network device, such asnetwork device 400 of FIG. 4. In other embodiments, process 1100 orportions of process 1100 of FIG. 11 may be implemented by and/orexecuted on a plurality of network devices, such as network device 400of FIG. 4. In yet other embodiments, process 1100 or portions of process1100 of FIG. 11 may be implemented by and/or executed on one or moreblade servers, such as blade server 250 of FIG. 2B.

Process 1100 begins, after a start block, at block 1102, where resourcesallocated for use by the Project may be determined to be sub-optimal.Such a determination may be made by many methods, including, rule-basedsystems, or manual systems. Embodiments may apply various rule-basedsystems that may enable determining that a project is operating withsuboptimal resources. Such rule-based systems may include, detecting ifa performance metric threshold has been exceeded, triggering resourceallocations based on schedule, triggering resource allocations based onpattern prediction that may indicate a potential change in utilizationrequirements, and the like. In addition, an operator may determine byobservation that resources are suboptimal.

Process 1100 next proceeds to block 1104, where, the optimal level ofproject resources may be determined. In some embodiments, optimalresources may be static or dynamic. In at least one embodiment, optimalresources may be automatically determined by rule-based systems,predictive computing techniques, or the like. In another embodiment,optimal resources may be manually determined by an operator. Thespecific allocation of resources may be determined in part by thecharacteristics of the project, or they may be determined by factorsexternal to project. For example, a project that requires a very largedataset may have an optimal resource allocation that emphasizesincreased data storage volume over processor performance.

Process 1100 continues at block 1106, where the project resources may bescaled to support the determined optimal level. Additional non-limitingembodiments of elastic scaling of project resources are described below.After block 1106, process 1100 may return control to a calling process.

FIG. 12 illustrates a logical flow diagram generally showing oneembodiment of a process for receiving resource allocation direction froman operator manipulating a user interface control. In some embodiments,process 1200 of FIG. 12 may be implemented by and/or executed on asingle network device, such as network device 400 of FIG. 4. In otherembodiments, process 1200 or portions of process 1200 of FIG. 12 may beimplemented by and/or executed on a plurality of network devices, suchas network device 400 of FIG. 4. In yet other embodiments, process 1200or portions of process 1200 of FIG. 12 may be implemented by and/orexecuted on one or more blade servers, such as blade server 250 of FIG.2B.

The user interface control may have a user interface that represents aslider, dial, selection lists, radio buttons, check boxes, and the like.Embodiments may be arranged to map various elastic scaling dimensions toa control. For example, a control may represent processing performance,index storage, time-window of received data, and the like. An embodimentof a use case of a slider user interface is described in more detailbelow in conjunction with FIG. 23.

Process 1200 begins, after a start block, at block 1202, where a controlchange (delta) may be received. In at least one embodiment, an operatormay change, or manipulate the control to provide the delta. In someembodiments, a signal, message, or notification from the control may bereceived indicating that a change in the control may have occurred(i.e., the delta).

Process 1200 proceeds next to decision block 1204, where a determinationmay be made whether the delta is greater than zero. In at least oneembodiment, a delta greater than zero may indicate a request to increaseresources for the instant project. If the delta is greater than zero,then process 1200 may flow to block 1206; otherwise, process 1200 mayflow to decision block 1208.

At block 1206, the resources for the project may be increased. Oneembodiment of a process for increasing resources for a project isdescribed in more detail below in conjunction with FIG. 13. After block1206, process 1200 may return control to a calling process.

If, at decision block 1204, the delta is not greater than zero, thenprocessing may flow from decision block 1204 to decision block 1208. Atdecision block 1208 a determination may be made whether the delta isless than zero. In at least one embodiment, a delta less than zero mayindicate a request to decrease resources for the instant project. If thedelta is less than zero, then process 1200 may flow to block 1210;otherwise, process 1200 may return control to a calling process.

At block 1210, the resources for the project may be decreased. Oneembodiment of a process for decreasing resources for a project isdescribed in more detail below in conjunction with FIG. 10.

Note, the concept of increasing or decreasing resources as used hereinis generalized to refer to increasing or decreasing project resources ina defined and configured “dimension.” Thus, it is important to recognizethat increasing project resources in a particular defined dimension mayactually require some computing resources to be increased while othermay be decreased. For example, if for an embodiment, a single projectresource elastic scaling dimension has been arranged such the increasinga slider (delta>zero) means to emphasize storage and de-emphasizeprocessing speed, then the effect may be to increase storage and reducethe CPU quota. Whereas, staying with this example, decreasing the slider(delta<zero) may mean to de-emphasize storage and emphasize processingspeed, then the effect may be to de-increase storage and increase theCPU quota. In some embodiments there may be a separate slider or controlfor many of the computing and performance attributes that make upproject resources.

One of ordinary skill in the art will appreciate that sliders andcontrols may be arranged and configured in many ways to provideoperators with a user-interface for controlling the elastic scaling ofproject resources. Embodiments may range from single controls thateffect many elements of the computing process with a single action, tomany fine grain controls that may be designed to elastically scaleindividual computing performance attributes. For example, an embodimentenabling fine grain control may have separate controls to adjust CPUquota, RAM use, disk access, network bandwidth, process priority, andthe like. Similarly, on the other end of the spectrum, an embodiment mayimplement a single high level control in the aggregate that may bearranged to hide and abstract the separate adjustments to CPU quota, RAMuse, disk access, network bandwidth, process priority, and the like. Inthe case of high-level controls the operator may not be required to haveknowledge that a single change in the high level control may affect manyof the project's resource components.

Next, process 1200 may return control to a calling process.

FIG. 13 illustrates a logical flow diagram generally showing oneembodiment of a process for increasing a project's resources as part ofelastic scaling. In some embodiments, process 1300 of FIG. 13 may beimplemented by and/or executed on a single network device, such asnetwork device 400 of FIG. 4. In other embodiments, process 1300 orportions of process 1300 of FIG. 13 may be implemented by and/orexecuted on a plurality of network devices, such as network device 400of FIG. 4. In yet other embodiments, process 1300 or portions of process1300 of FIG. 13 may be implemented by and/or executed on one or moreblade servers, such as blade server 250 of FIG. 2B.

Process 1300 begins, after a start block, at block 1302, whereparticular computing resources that correspond to the requested increasein resources may be determined. As discussed above a requested increaseof resources may be a simple request to increase a single component ofthe computing system, such as CPU quota, or it may represent an increasein an elastic scaling dimension that may require the adjustment andreallocation of more than one component in the computing system, suchas, CPU quota, RAM quota, network bandwidth quota, and the like. In someembodiments, an increase of one resource may result in a decrease ofanother resource.

Process 1300 next proceeds to block 1304, where the impact that therequested resources may have on the project, other projects, and/or thesystem in general may be determined. In some embodiments, the impact ofthe requested resources may be static or dynamic. In at least oneembodiment, the impact may be automatically determined by rule-basedsystems, predictive computing techniques, or the like. In anotherembodiment, the impact may be manually determined by an operator.

Embodiments may be arranged to define rules and thresholds that may setlimits on the resources that may be allocated to individual projects.Also, rules may be arranged to determine minimum resources that may bemade available for other projects in the system. One of ordinary skillin the art will appreciate that there may be many factors that may beavailable for analysis when determining if the requested increase ofresources may cause unacceptable impact on the project, projects, and/orthe system in general. For example, a request to increase index storagesize to a very large size may cause such a large data set to be createdthat the project may not have CPU quota, or RAM quota to effectivelyprocess the large dataset. How a condition like this is handled dependson how the embodiment is arranged and configured. In some cases, such anincrease in project resources may be aborted because it is out ofbounds. In other cases, referring to the example above, an embodimentmay determine the necessary CPU quota and RAM quota that may benecessary to keep up with the projected increased index storage size.

After the necessary resources for the requested increase of resourceshas been determined process 1300 continues at decision block 1306, wherea determination may be made whether there is global headspace availablefor the requested increase of resources. In at least one embodiment,this determination may be made by testing the amount of global headspaceavailable. This test may take into account all of the resourcesavailable and provisioned for the operator or process that is requestingthe increase of resources for the project. For example, an embodimentmay require users to supply a pre-authorization when requested resourceswould increase a user's total usage of system resources beyond a certainlevel. Or, an embodiment may be configured to require an administrativeuser to authorize any resource increase request that may increase totalresource use beyond a configured level. In any event, an embodiment maytest whether the global conditions may be able to absorb the requestedincrease in resources.

In at least one embodiment, if there is insufficient global headspaceavailable, then the requested increase in the resource may not beexecuted at the time of the request. In some embodiments, if the globalheadspace for the requested increase of resources is available, thenprocess 1300 may flow to decision block 1308; otherwise, process 1300may flow to block 1312. In some other embodiments, if the increase inresources would exceed global thresholds and/or limitations, then therequest for the increase of resources may be discarded.

Process 1300 continues at decision block 1308, where a determination maybe made whether the local resources related to the project may becapable of handling the requested increase in project resources. Forexample, in an embodiment that may be employing virtual machines, therequested increase in project resources may require that a virtualmachine allocate more virtual disk space, or it may require that thevirtual machine be migrated to another physical machine that may be ableto accommodate the requested increase in project resources. In someembodiments, if such operations are unable to be resolved immediately(e.g., within a predefined time period), then the local resources maynot be capable of handling the requested increase of project resources.If the local resources are capable of handling the requested increase inproject resources, then process 1300 may flow to decision block 1310;otherwise, process 1300 may flow to block 1312 to queue the request.

At decision block 1310, a determination may be made whether therequested increase in project resources may be arranged or configured tooccur at a scheduled time in the future. In some embodiments, a userand/or operator may determine a scheduled time when the requestedincrease may occur. In other embodiments, the scheduled time may bepredetermined, such as five minutes from when the request was received.In other embodiments, the scheduled time may be based on the resourcesrequested. For example, if additional CPU quota is requested, then thescheduled time may be one minute from when the request was received,where a request for additional storage space may be scheduled 10 minutesfrom when the request was received. If the increase may be scheduled tooccur in the future, then process 1300 may flow to block 1312 to queuethe request; otherwise, process 1300 may flow to block 1314.

At block 1312, the request for the increase of resources may besubmitted to a queue. In at least one embodiment, the request may remainin the queue until conditions allow it to be fulfilled (i.e., availableresources). One embodiment of queuing project resource requests isdescribed in more detail below in conjunction with FIG. 15. In someembodiments, a process or operator requesting an increase in projectresources may not have knowledge of the global resource allocation.Queuing the requested increase in project resources may enable shortrunning processes to finish and expire so that their released resourcesmay be made available to a queued request for increasing projectresources. After block 1312, process 1300 may return control to acalling process.

If the requested increase in project resources is not queued, thenprocess 1300 may flow to block 1314. At block 1314, the determinedresources for the requested increase may be allocated. Embodiments forallocating resources are discussed in more detail below in conjunctionwith FIGS. 16-18.

After block 1314, process 1300 may return control to a calling process.

FIG. 14 depicts a logical flow diagram generally showing one embodimentof process for responding to a requested decrease in project resources.In some embodiments, process 1400 of FIG. 14 may be implemented byand/or executed on a single network device, such as network device 400of FIG. 4. In other embodiments, process 1400 or portions of process1400 of FIG. 14 may be implemented by and/or executed on a plurality ofnetwork devices, such as network device 400 of FIG. 4. In yet otherembodiments, process 1400 or portions of process 1400 of FIG. 14 may beimplemented by and/or executed on one or more blade servers, such asblade server 250 of FIG. 2B.

In some embodiments, a requested decrease in project resources mayrequire some system or computing resources to decrease while others maybe required to be increased depending on how the relevant controldimension has been arranged and configured.

Process 1400 begins, after a start block, at decision block 1402, wherea determination may be made whether the requested decrease in projectresources may be scheduled to occur in the future. In at least oneembodiment, decision block 1402 may employ embodiments of decision block1310 of FIG. 13 to determine if a request may be scheduled to occur at atime after the request is received. If the decrease in project resourcesmay be scheduled in the future, then process 1400 may flow to block 1410to queue the request at least until the scheduled time; otherwise,process 1400 may flow to block 1404.

At block 1404, the impact of the request on the project, other projects,and/or the system as a whole may be determined. In at least oneembodiment, block 1404 may employ embodiments of block 1304 of FIG. 13to determine an impact of resources on the project and the system(noting that block 1304 of FIG. 13 determines based on an increase inresources and block 1404 determines based on a decrease in resources).

Process 1400 next proceeds to decision block 1406, where a determinationmay be made whether the impact of the requested decrease in projectresources is unacceptable. In at least one embodiment, running processesof the current project may be analyzed to determine if they can run tocompletion under the conditions of the decreased resources. In onenon-limiting, non-exhaustive example, a current project may not run tocompletion if the decrease in resources starves the project of processortime, which may be determined to be unacceptable. If the requesteddecrease in project resources is acceptable, then process 1400 may flowto block 1408; otherwise, process 1400 may flow to block 1410 to queuethe request, which may enable the current processes to finishgracefully. But, in some embodiments a requested decrease in projectresource may be arranged and configured so it may not cooperate with therunning processes. In such cases, an embodiment may terminate therunning process to avoid unpredictable outcomes that may occur if theprocesses try to continue to run reduced resource environment.

At block 1410, the resource decrease request may be queued. Anembodiment of a project resource request queue is shown in FIG. 15. Asdiscussed above project resource requests may be submitted to a requestqueue if the request may not be completed at the time it may beinitiated. This may occur for many reasons, including lack of local orglobal resources, lack of authorizations that may be needed, the requestmay be deliberately schedule to occur in the future, currently runningprocesses may be blocking the request, and the like.

A project resource request queue may be arranged to hold request recordsthat may comprise a data structure that carries the metadata that maycontain the information about the resources that may have beendetermined necessary to execute the request. Such metadata may includeinstructions on how to allocate resources for all of the componentsimpacted by the resource request. For example, a project resourcerequest may require a CPU quota adjustment and index storage sizeallocation as part of a single project resource request. In a case likethis, a queued resource request may contain metadata and instructionsthat may be used to executed the CPU quota change and the index storageallocation. In other embodiments the queued request may contain thecontrol delta information from the component that initiated the projectrequest and the underlying components and instructions needed to executethe request may be determined at the time of allocation.

If, at decision block 1406, the requested decrease in project resourcesis acceptable, then process 1400 may flow from decision block 1406 toblock 1408. At block 1408, resource allocation for the current projectmay be decreased. Embodiments for allocating resources are discussed inmore detail below in conjunction with FIGS. 16-18.

After block 1408, process 1400 may return control to a calling process.

FIG. 15 illustrates a logical flow diagram generally showing oneembodiment of process for queuing resource requests. In someembodiments, process 1500 of FIG. 15 may be implemented by and/orexecuted on a single network device, such as network device 400 of FIG.4. In other embodiments, process 1500 or portions of process 1500 ofFIG. 15 may be implemented by and/or executed on a plurality of networkdevices, such as network device 400 of FIG. 4. In yet other embodiments,process 1500 or portions of process 1500 of FIG. 15 may be implementedby and/or executed on one or more blade servers, such as blade server250 of FIG. 2B.

Process 1500 begins, after a start block, at decision block 1502, wherea determination may be made whether there are queued requests. In atleast one embodiment, this determination may be based on whether thequeue is holding any requests. If the queue is holding requests, thenprocess 1500 may flow to block 1504; otherwise, process 1500 may returncontrol to a calling process.

At block 1504, a next request in the queue may be examined. In at leastone embodiment, this request examination may include a determination ofthe resources associated with the next request and a determination ofthe conditions that need to be met for the next request to be acted upon(e.g., acceptable resources available to accommodate the request). Insome embodiments, the conditions may include the conditions that led tothe next request being entered into the request queue in the firstplace. For example, the condition may include a scheduled time.

Process 1500 next proceeds to decision block 1506, where a determinationmay be made whether the conditions to execute the next request aresatisfied for the next request. For example, a next request thatrequired prior authorization before proceeding may be tested to see ifsufficient authorization has been obtained. Or, global resourceconditions may be examined to determine if a next request that may havebeen queued because of a lack of available global resources now may havesufficient resources available to proceed. For next requests that mayhave been queued so they may occur at a scheduled time in the future thetime may be checked. If the conditions for the next request are met,then process 1500 may flow to block 1508; otherwise, process 1500 mayloop to decision block 1502. If conditions for the next request are notmet, the process may leave the request in the queue and may examine thenext request in the queue. In some embodiments a queue may be configuredsuch that if a request remains in the queue longer that a specified timean additional action may be taken. Such actions may include, notifyingthe operator, generating alerts in the form of log messages or othernotifications, removing the request from the queue, and the like.

At block 1508, the determined resources based on the next request may beallocated. Embodiments for allocating resources are discussed in moredetail below in conjunction with FIGS. 16-18.

Process 1500 continues at block 1510, where the completed request may beremoved from the queue. In some embodiments, the next request may beconfigured to be returned to the queue after it has executed. Somerequests may be scheduled to occur at a certain time each day. Theserequests may be returned to the queue to wait until the next time toexecute. Other requests may be considered “standing” requests that mayremain in the queue waiting for certain conditions to be met. Forexample, an embodiment may be arranged to automatically increase indexstorage as it is needed. In this kind of case, an embodiment may use aqueued request that may execute when it determines that more indexstorage is needed.

Embodiments may be arranged to have multiple project resource requestqueues designated for different types of requests. Also, embodiments mayemploy general purpose queues that may be used for queue projectresource requests as well as other types of requests and events.

After block 1510, process 1500 may return control to a calling process.

As discussed briefly above, embodiments may be arranged to supportelastic scaling in one or more dimensions. FIG. 16 depicts a logicalflow diagram generally showing one embodiment of process for elasticallyscaling based on index storage size. In some embodiments, process 1600of FIG. 16 may be implemented by and/or executed on a single networkdevice, such as network device 400 of FIG. 4. In other embodiments,process 1600 or portions of process 1600 of FIG. 16 may be implementedby and/or executed on a plurality of network devices, such as networkdevice 400 of FIG. 4. In yet other embodiments, process 1600 or portionsof process 1600 of FIG. 16 may be implemented by and/or executed on oneor more blade servers, such as blade server 250 of FIG. 2B

Process 1600 begins, after a start block, at block 1602, where anoptimal storage size for a new index store may be determined. In someembodiments, optimal storage size may be static or dynamic. In at leastone embodiment, optimal storage size may be automatically determined byrule-based systems, predictive computing techniques, or the like. Inanother embodiment, optimal storage size may be manually determined byan operator.

The optimal size may be determined by a rule-based system tailored tothe specific project that owns the index store. An embodiment of arule-based system for elastic scaling may employ triggers linked toperformance and resource thresholds. Different projects may beconfigured to have different triggers and different thresholds dependingon the requirements of the project. In addition to rule-baseddetermination, the optimal size for index store may be determined by anoperator using a user-interface control such as a slider, dial, radiobuttons, and the like. Even though an operator has used a control todetermine the optimal size, an embodiment may translate the operation ofthe control into the actual optimal index store size. For example, anoperator may use a user interface to control to increase an index storefrom 5 gigabytes to 10 gigabytes. In this case an embodiment may have tomake several determinations to account for the actual storage sizeneeded to account for administration overhead that may not be apparentto the operator.

Process 1600 continues at block 1604, where new storage may be allocatedand/or formatted to accommodate the elastic scaling of the index store.New storage may be created so the current index store may not be alteredor disturbed during the elastic scaling process.

Process 1600 proceeds next to block 1606, where new objects and/orprocesses may be allocated and/or instantiated to optimally service thescaled new index store. Embodiments may create new objects and processesto avoid disturbing the current index store during the elastic scalingprocess.

Continuing at block 1608, the new index store may be determined. Atleast one embodiment for determining a new index store is described inmore detail below in conjunction with FIG. 19. Briefly, however, in someembodiments indexers may be activated (i.e., marked as read/write) ordeactivated (i.e., marked as read-only based on a number of indexersneeded for the scaled new index store storage. In some otherembodiments, the current index store may be marked as read-only and thenew index store may be generated from new indexers. This may ensure thatthe all new writes to the index store may be written into the scaled newindex store storage.

Process 1600 next proceeds to block 1610, which is discussed in moredetail below in conjunction with FIG. 22. Briefly, however, at block1610, an input proxy may be directed to use the scaled new index storefor the indexing of incoming events.

Process 1600 continues at block 1612, where the new objects and/orprocesses may be employed to index incoming events using the scaled newindex store. In at least one embodiment, incoming events and/or incomingdata may include new events/data and/or archived events/data.

In at least one embodiment, the scaled new index store may be utilizedbased on Roles of the new indexes. In some embodiments, new indexes(which may include the new objects, new processes, or the like) may beautomatically added to existing indexes (which may include the existingobjects, existing processes, or the like). In at least one embodiment,the new indexes may be attached to and/or inherit Roles associated withthe existing indexes for at least one Core User of the project. In suchan embodiment, the input proxy may utilize the inherited Roles during ascaling event to determine when to send incoming events (and/or otherdata) to the new indexes. As described above, the Roles may determineaccess controls to the indexes.

After block 1612, process 1600 may return control to a calling process.

FIG. 17 depicts a logical flow diagram generally showing one embodimentof a process for elastically scaling based on indexing performance. Insome embodiments, process 1700 of FIG. 17 may be implemented by and/orexecuted on a single network device, such as network device 400 of FIG.4. In other embodiments, process 1700 or portions of process 1700 ofFIG. 17 may be implemented by and/or executed on a plurality of networkdevices, such as network device 400 of FIG. 4. In yet other embodiments,process 1700 or portions of process 1700 of FIG. 17 may be implementedby and/or executed on one or more blade servers, such as blade server250 of FIG. 2B.

Indexing performance may be a compound elastic scaling dimension thatmay be generally related to speed of the processing for a project. Formany embodiments multiple component resources, such CPU quota, networkbandwidth quota, RAM quota, index storage, and like, may be scaled toexecute elastic scaling based on Indexing Performance.

Process 1700 begins, after a start block, at block 1702, where resourcesneeded for optimal indexing performance may be determined. In at leastone embodiment, optimal indexing performance may be automaticallydetermined by rule-based systems, predictive computing techniques, orthe like. In another embodiment, optimal indexing performance may bemanually determined by an operator.

The specific resources needed may be determined by a rule-based systemtailored to a specific project. An embodiment of a rule-based system forelastic scaling may employ triggers linked to performance and resourcethresholds. Different projects may be configured to have differenttriggers and different thresholds depending on the requirements of theproject. In addition to rule-based determination the optimal resourceallocation may be determined by an operator using a user-interfacecontrol such as a slider, dial, radio buttons, and the like. Even thoughan operator may use a control to determine the optimal indexingperformance an embodiment may translate the operation of the controlinto the actual optimal allocation of resources. For example, anoperator may use a user interface to control to increase a projectsindexing performance from “low” to “high.” However, in this case anembodiment may have to make several determinations to account for CPUquota, disk access quota, RAM quota, storage size, and the like, thedetails of which may not be apparent to the operator.

Process 1700 proceeds to block 1704, where new storage may be allocatedand/or formatted to accommodate the elastic scaling of the indexingperformance. An embodiment may allocate and format a new storage even ifthe size of the data store has not increase or decrease. New storage maybe created so the current index store may not be altered or disturbedduring the elastic scaling process.

Processing continues at block 1706, where new objects and/or processesmay be allocated and/or instantiated to optimally support the determinedindexing performance requirements. Embodiments may create new objectsand processes to avoid disturbing the current index store during theelastic scaling process.

Process 1700 proceeds next at block 1708, where the new index store maybe determined. In at least one embodiment, block 1708 may employembodiments of block 1608 of FIG. 16 to determine the new index store.

Process 1700 continues next at block 1710, which is discussed in moredetail below in conjunction with FIG. 22 Briefly, however, at block1710, an input proxy may be directed to use the scaled new index storefor the indexing of incoming events.

Process 1700 proceeds to block 1712, where the new objects and/orprocesses may be employed to index incoming events using the scaled newindex store. In at least one embodiment, incoming events and/or incomingdata may include new events/data and/or archived events/data. In atleast one embodiment, block 1712 may employ embodiments of block 1612 ofFIG. 16 to use the scaled new index store.

After block 1712, process 1700 may return control to a calling process.

FIG. 18 depicts a logical flow diagram generally showing one embodimentof a process for elastically scaling based on an event time window. Insome embodiments, process 1800 of FIG. 18 may be implemented by and/orexecuted on a single network device, such as network device 400 of FIG.4. In other embodiments, process 1800 or portions of process 1800 ofFIG. 18 may be implemented by and/or executed on a plurality of networkdevices, such as network device 400 of FIG. 4. In yet other embodiments,process 1800 or portions of process 1800 of FIG. 18 may be implementedby and/or executed on one or more blade servers, such as blade server250 of FIG. 2B.

Event time window may be a compound elastic scaling dimension that maybe generally related to the index storage sizes for a project. Anembodiment may be arranged to receive data such that the index store maybe sufficient to hold data received during a determined time window. Atime window may be described as date-time expression such as, a startdate-time and an end date-time, a duration, such as 30 days, startdate-time plus a duration, and the like. For many embodiments multiplecomponent resources, such CPU quota, network bandwidth quota, RAM quota,index storage, and like, may be scaled to execute elastic scaling basedon event time windows.

Process 1800 begins, after a start block, at block 1802, where a newevent time window may be determined. The event time window may besubmitted as a complete time duration expression or it may bedynamically determined based on past event traffic and predicted futureevent traffic or any method to describe a time window for capturingevents.

Process 1800 proceeds next to block 1804, where resources needed forindexing data for the determined event time window may be determined.The specific resources needed may be determined by a rule-based systemtailored for specific projects. An embodiment of a rule-based system forelastic scaling may employ triggers linked to performance and resourcethresholds. Different projects may be configured to have differenttriggers and different thresholds depending on the requirements of theproject. In addition to rule-based determination, the optimal resourceallocation may be determined by an operator using a user-interfacecontrol such as a slider, dial, radio buttons, and the like. Even thoughan operator may use a control to determine the optimal indexingperformance an embodiment may translate the operation of the controlinto the actual optimal allocation of resources. For example, anoperator may use a user interface control to increase a project's eventtime window from “10 days” to “30 days.” However, in this case anembodiment may have to make several determinations to account for CPUquota, disk access quota, RAM quota, storage size, and the like, thedetails of which may not be apparent to the operator.

In any event, process 1800 continues at block 1806, where new storagemay be allocated and/or formatted to accommodate the elastic scaling ofthe determined event time window in the new index store. New storage maybe created so the current index store may not be altered or disturbedduring the elastic scaling process.

Process 1800 proceeds to block 1808, where new objects and/or processesmay be allocated and/or instantiated to optimally support the determinedevent time window. Embodiments may create new objects and processes toavoid disturbing the current index store during the elastic scalingprocess.

Continuing to block 1810, the new index store may be determined. In atleast one embodiment, block 1708 may employ embodiments of block 1608 ofFIG. 16 to determine the new index store.

Process 1800 proceeds next to block 1812, which is discussed in moredetail below in conjunction with FIG. 22. Briefly, however, at block1812, an input proxy may be directed to use the scaled new index storefor the indexing of incoming data.

Process 1800 continues to block 1814, where the new objects and/orprocesses may be employed for indexing incoming data using the scalednew index store. In at least one embodiment, incoming events and/orincoming data may include new events/data and/or archived events/data.In at least one embodiment, block 1814 may employ embodiments of block1612 of FIG. 16 to use the scaled new index store.

After block 1814, process 1800 may return control to a calling process.

FIG. 19, illustrates a logical flow diagram generally showing oneembodiment of a process for changing a number of indexers associatedwith an index store. In some embodiments, process 1900 of FIG. 19 may beimplemented by and/or executed on a single network device, such asnetwork device 400 of FIG. 4. In other embodiments, process 1900 orportions of process 1900 of FIG. 19 may be implemented by and/orexecuted on a plurality of network devices, such as network device 400of FIG. 4. In yet other embodiments, process 1900 or portions of process1900 of FIG. 19 may be implemented by and/or executed on one or moreblade servers, such as blade server 250 of FIG. 2B.

Although process 1900 describes changing a number of indexers, in someembodiments, changing a number of indexers (e.g., indexer servers) mayalso include changing an amount of resources associated with a project,such as, for example, storage, objects, processors, or the like. In atleast one embodiment, adding additional indexers may include addingadditional storage space and/or processors (and/or other resources). Inanother embodiment, reducing a number of indexers may include reducingstorage space and/or processors (and/or other resources. In yet otherembodiments, resources for a given indexer server may also be changed.In some embodiments, resources of an indexer server may be changed bychanging a number of indexes used by a project, which may also change anamount of storage, processing capacity, or the like for the project.

Process 1900 begins, after a start block, at decision block 1902, wherea determination may be made whether additional indexers may be added tothe index store. In at least one embodiment, the determination may bebased on the elastic scaling. In some embodiments, if the storage sizeand/or the performance are increased, then indexers may be added to theindex store. If indexers may be added to the index store, then process1900 may flow to decision block 1904; otherwise, process 1900 may flowto decision block 1906.

At decision block 1906, a determination may be made whether to removeindexers from the index store. In at least one embodiment, thedetermination may be based on the elastic scaling. In some embodiments,if the storage size and/or the performance are decreased, then indexersmay be removed from the index store. If indexers may be removed from theindex store, then process 1900 may flow to block 1908; otherwise,process 1900 may return control to a calling process.

At block 1908, at least one indexer may be deactivated. In someembodiments, de-activating an indexer may include marking the indexer asread-only. In at least one embodiment, a read-only indexer may indicatethat the indexer is not currently active for the new index store. Insome embodiments, a determination may be made on which indexers todeactivate based on time (e.g., creation time, last modified time, lastaccess time, or the like), size of the indexer, or the like. In at leastone embodiment, a user may be prevented from accessing a deactivatedindexer. In some embodiments, if the indexer is deactivated for a periodof time, then the data may be removed from the deactivated indexer(e.g., deleted and/or moved to archival storage).

If, at decision block 1902, additional indexers may be added to theindex store, then processing may flow from decision block 1902 todecision block 1904. At decision block 1904, a determination may be madewhether there are deactivated indexers (such as were deactivated atblock 1908). If there are deactivated indexers, then process 1900 mayflow to block 1912; otherwise, process 1900 may flow to block 1910.

At block 1912, at least one currently deactivated indexer may beactivated and added to the new index store. In at least one embodiment,activating may include marking a read-only indexer as a read/writeindexer. After block 1912, process 1900 may return control to a callingprocess.

If, at decision block 1904, there are no deactivated indexers, thenprocess 1900 may flow from decision block 1904 to block 1910. At block1910, new indexers may be added to the new index store. After block1910, process 1900 may return control to a calling process.

FIG. 20 shows a logical flow diagram generally showing one embodiment ofa process to recall archived data for re-indexing. In some embodiments,process 2000 of FIG. 20 may be implemented by and/or executed on asingle network device, such as network device 400 of FIG. 4. In otherembodiments, process 2000 or portions of process 2000 of FIG. 20 may beimplemented by and/or executed on a plurality of network devices, suchas network device 400 of FIG. 4. In yet other embodiments, process 2000or portions of process 2000 of FIG. 20 may be implemented by and/orexecuted on one or more blade servers, such as blade server 250 of FIG.2B.

Embodiments may be arranged to archive input data as it is indexed.(See, input proxy, as shown in FIG. 22, for more details aboutarchiving.) Data stored in the archives may be in the same format andform as it was sent to the input proxy. A process may process data fromthe archive and create indexes from the data. This may enable operatorsto re-create indexes from the archived data and it may enable operatorsto create new indexes that may be processed differently from the indexesthat may have been created when the data was first received.

Process 2000 begins, after a start block, at block 2002, where a timewindow of events may be determined for re-indexing. The time windows maybe determined be a rule-based algorithm that may automatically determinethe time window or an operator may select the time window manually usinga user interface.

Process 2000 continues at block 2004, where event data records may beretrieved from the archive.

Process 2000 proceeds next to block 2000, where the retrieved event datarecords are indexed using the current project's parameters. Recall ofarchived event data may occur in the context of a new project or it mayoccur as part of an existing project.

Processing continues at decision block 2008, where a determination maybe made whether, there are additional records remaining in the archive.In some embodiments, the process may continue to retrieve records andindex them from the archive until all the data within the determinedtime window has been exhausted. In some embodiments a recall process maybe aborted or paused based on operator intervention or when determinedperformance thresholds have been reached. If there are records remainingin the archive, then process 2000 may loop to block 2004; otherwise,process 2000 may return control to a calling process.

As described above, a new scaled index store may be employed based onelastic scaling. In some embodiments, data from a previous index storemay remain available while the new scaled index store is employed. FIG.21 illustrates a logical flow diagram generally showing one embodimentof a process for transitioning to scaled index stores. In someembodiments, process 2100 of FIG. 21 may be implemented by and/orexecuted on a single network device, such as network device 400 of FIG.4. In other embodiments, process 2100 or portions of process 2100 ofFIG. 21 may be implemented by and/or executed on a plurality of networkdevices, such as network device 400 of FIG. 4. In yet other embodiments,process 2100 or portions of process 2100 of FIG. 21 may be implementedby and/or executed on one or more blade servers, such as blade server250 of FIG. 2B.

Process 2100 begins, after a start block, at block 2102, where eventdata may be received from an input proxy. Embodiments of employing aninput proxy are described in more detail below in conjunction with FIG.22.

Process 2100 next proceeds to block 2104, where the received event datamay be indexed. In at least one embodiment, the indexed event data maybe stored in the new scaled index store.

Process 2100 continues at block 2106, where the total storage for thenew events stored in the scaled new index store and the old event thatmay be stored in the previously used read-only index store may bedetermined. Proceeding to decision block 2108, a determination may bemade whether the total amount of storage used is greater than the amountof stated provisioned for the project. If the total storage used isgreater than the amount of storage provisioned for the project, thenprocess 2100 may flow to block 2110; otherwise, process 2100 may loopback to block 2102 to receive additional event data from the InputProxy.

At block 2110, the index records in the previously provisioned storagemay be marked for archival or removal. For the index records marked forarchival, process 2100 may flow to block 2112; for the index recordsmarked for removal, process 2100 may flow to block 2114.

At block 2110, the index records marked for archival may be copied fromthe previously provisioned storage to archival storage.

At block 2114, the index records marked for removal may be deleted fromthe previously provisioned storage. In some embodiments, index recordsmarked from archive may be deleted from the previously provisionedstorage after being copied to the archival storage.

After block 2114, process 2100 may return control to a calling process.

As described above, some embodiments may enable the operation of aninput proxy. FIG. 22 illustrates a logical flow diagram generallyshowing one embodiment of an input proxy operation. In some embodiments,process 2200 of FIG. 22 may be implemented by and/or executed on asingle network device, such as network device 400 of FIG. 4. In otherembodiments, process 2200 or portions of process 2200 of FIG. 22 may beimplemented by and/or executed on a plurality of network devices, suchas network device 400 of FIG. 4. In yet other embodiments, process 2200or portions of process 2200 of FIG. 22 may be implemented by and/orexecuted on one or more blade servers, such as blade server 250 of FIG.2B.

Process 2200 begins, after a start block, at block 2202 where the proxymay receive data. The data may be received from remote clients andsources. The data source may stream the data to the input proxy usingvarious networking technologies, including, Ethernet, 802.11(a, b, g,and n), Bluetooth, TCP/IP, UDP, HTTP, internal specific point-to-pointprotocol, and the like. In some embodiments, the proxy may throttle(increase or decrease) a rate at which data incoming data is streamed.In at least one embodiment, the data rate may be based on acorresponding project. For example, the data rate may be based on anamount of storage space allocated for the project (e.g., an amount ofstorage space purchased by a user for the project). The data may bereceived and a process may “tee” the data, sending it down at least twopaths at the same time, which may be depicted in FIG. 22 as Path A andPath B.

Proceeding on Path A, process 2200 may proceed from block 2202 to block2204. At block 2204, the raw data may be load balanced to determinewhich indexer to use.

Process 2200 continues next at block 2206, where the received data maybe indexed on the load balanced indexers. In some embodiments, a size ofeach indexer may not be limited. In other embodiments, the size of eachindexer may be limited. In one such embodiment, an amount of data perindexer may be monitored. In one embodiment, the monitoring may beasynchronous to incoming data. In some embodiment, if a limit for anindexer is reached or almost reached (e.g., less than 5% remaining),then a message may be sent to a user to indicate that the indexer limitis reached or almost reached.

In some other embodiments, indexing may be disabled if a user exceedspurchased resource allocation. In at least one embodiment, indexing maybe disabled if a user and/or project exceeds an allocated storage size(e.g., previously purchased amount of storage). In another embodiment,indexing may be disabled if a user discontinues paying for the indexing.In yet another embodiment, indexing may be disabled if a user and/orproject exceeds a number of buckets for the project.

Process 2200 next proceeds to block 2208, where the indexed data andevent records may be stored in the project's index store.

Proceeding on Path B, process 2200 may proceed from block 2202 to block2210. At block 2210, the raw data may be sent to be copied tointermediate storage. The intermediate storage may be arranged to beavailable, fast and reliable. Embodiments may employ a FIFO bufferimplemented by local hard disks, RAID arrays, and the like, to ensurethat the raw data is not lost.

Process 2200 continues at block 2212, where the data may be archived asarchival storage becomes available. Moving the raw data from theintermediate storage to the long term archive may be executed by aseparate process that reliably moves the raw data from the intermediatestorage to the long term storage. After block 2208 and 2212, process2200 may return control to a calling process.

It will be understood that each block of the flowchart illustration, andcombinations of blocks in the flowchart illustration, can be implementedby computer program instructions. These program instructions may beprovided to a processor to produce a machine, such that theinstructions, which execute on the processor, create means forimplementing the actions specified in the flowchart block or blocks. Thecomputer program instructions may be executed by a processor to cause aseries of operational steps to be performed by the processor to producea computer-implemented process such that the instructions, which executeon the processor to provide steps for implementing the actions specifiedin the flowchart block or blocks. The computer program instructions mayalso cause at least some of the operational steps shown in the blocks ofthe flowchart to be performed in parallel. Moreover, some of the stepsmay also be performed across more than one processor, such as mightarise in a multi-processor computer system. In addition, one or moreblocks or combinations of blocks in the flowchart illustration may alsobe performed concurrently with other blocks or combinations of blocks,or even in a different sequence than illustrated.

Accordingly, blocks of the flowchart illustration support combinationsof means for performing the specified actions, combinations of steps forperforming the specified actions and program instruction means forperforming the specified actions. It will also be understood that eachblock of the flowchart illustration, and combinations of blocks in theflowchart illustration, can be implemented by special purposehardware-based systems, which perform the specified actions or steps, orcombinations of special purpose hardware and computer instructions.

Use Case Illustration

FIG. 23 illustrates a non-exhaustive example of a use case of anembodiment of user-interface controls that may be employed to enableelastic scaling. As shown in FIG. 23, an embodiment may be arranged toprovide user-interface controls, such as sliders, dials, radio buttons,spinners, touch controls, gesture controls, and the like, that mayenable an operator to elastically scale resources that may be associatedwith a project. One exemplary user-interface is shown in the FIG. 23.This may represent a user-interface having three slider controls forcontrolling the resource for the project.

As shown in FIG. 23, a slider control (e.g., control 2302, control 2304,and/or control 2306) may generally comprise a slider 2308 and a sliderthumb 2310. An operator may manipulate the slider thumb 2310 by movingit forward or backwards lengthwise within the slider 2308. The movementof the slider thumb 2310 may generate intermediate values that may beused for determining corresponding to elastic scaling values.

The embodiment depicted in FIG. 23 has three slider controls. Control2302, on the top of the figure, may be use for the elastic scaling ofindex storage size. Control, in the center of the figure, may be usedfor the elastic scaling of the number of server instances the may beused to support a project. And, control 2306, at the bottom of thefigure, may be used to set the index storage size by event time window.

Control 2302 may also include text box 2312 and text box 2314. In atleast one embodiment, text box 2312 may display the current valuerepresented by the position of slider thumb 2310 in slider 2308. In someother embodiments, text box 2312 may enable a user to enter a desiredvalue, and slider thumb 2310 may automatically slide to thecorresponding position in slider 2308.

In another embodiment, text box 2314 may display how much the currentvalue (i.e., what is displayed in text box 2312) of control 2302 willcost the owner of the project. In some other embodiments, text box 2314may enable a user to enter a desired cost, and slider thumb 2310 mayautomatically slide to the corresponding position in slider 2308. Asshown, each slider control may include text box 2312 and/or text box2314. However, it should be appreciated that embodiments are notrestricted to arranging text boxes as depicted herein. Embodiments maybe expected to use a variety of user interface methods to indicate thecurrent value of the controls and well as how much the selected valuemay cost. Also, embodiments may be arranged to display values differentand in addition to those depicted herein, or none at all.

Some embodiments may arrange for the user interface controls to usedifferent scales for the variables different that may be represented bythe control, such as, linear (as illustrated by control 2302),logarithmic (as illustrated by control 2306), parametric (as illustratedby control 2304), and the like. An embodiment may be arranged to use aparticular scale based on the type of user-interface being used and theresource that may be represented. In some cases, the scale of thecontrol may be determined based on how the user may be charged for theunderlying resource. For example, if a linear increase in the number ofserver instances many have a logarithmic increase in the cost to theuser it may be advantageous to scale the control to account for thechange in cost rather than the change in resources.

In some embodiments multiple controls may be linked together such thatadjusting one control may cause another control to adjust as well. Also,embodiments may provide additional user controls (not shown), such as,checkboxes, that may enable a user to lock a control so it may remain ina fixed position as other controls are adjusted.

In other embodiments, some controls may represent high level,generalized, or aggregated representations of resources, in this case auser may select a higher level control and “drill-down” into theunderlying elements that the high level, generalized, or aggregatedcontrol may be representing.

One of ordinary skill in the art will appreciate that the three controlsdepicted in the embodiment shown in FIG. 23 are merely exemplary andmany other configurations and arrangements could be used.

The above specification, examples, and data provide a completedescription of the composition, manufacture, and use of the invention.Since many embodiments of the invention can be made without departingfrom the spirit and scope of the invention, the invention resides in theclaims hereinafter appended.

1. A method for managing resources with at least one network device,comprising: determining a resource allocation for indexing data providedfor a project for each of a plurality of resources, wherein theresources includes at least one indexer server that indexes the provideddata and a data store that stores the indexed data; providing a requestfrom a user to scale at least one of the plurality of resources;adjusting the resource allocation for at least one of the plurality ofresources based on the request, wherein at least one of the plurality ofresources are changed based on the adjusted resource allocation; andemploying the changed plurality of resources to subsequently index dataprovided for the project.
 2. The method of claim 1, wherein adjustingthe resource allocation further comprises allocating at least one typeof additional resource if the request indicates an increase in theplurality of resources.
 3. The method of claim 1, wherein adjusting theresource allocation further comprises allocating less of at least onetype of resource if the change indicates a decrease in the plurality ofresources.
 4. The method of claim 1, further comprising: enabling theuser of the project to manually employ a control to request scaling ofat least one of the plurality of resources.
 5. The method of claim 1,wherein changing at least one of the plurality of resources includes atleast one of: changing a number of indexer servers employed to indexdata for the project; changing an amount of storage for the data storeto store data for the project; changing an amount of memory employed toprocess the indexing of data for the project; or changing an amount ofprocessors employed to process the indexing of data for the project. 6.The method of claim 1, wherein changing at least one of the plurality ofresources includes at least one of: activating at least one previouslydeactivated indexer server by marking at least one read-only indexerserver as a read and write indexer server; or deactivating at least oneindexer server by marking the at least one indexer server as read-only.7. A network device for managing resources, comprising: a memory forstoring data and instructions; and a processor that executes theinstructions to enable actions, including determining a resourceallocation for indexing data provided for a project for each of aplurality of resources, wherein the resources includes at least oneindexer server that indexes the provided data and a data store thatstores the indexed data; providing a request from a user to scale atleast one of the plurality of resources; adjusting the resourceallocation for at least one of the plurality of resources based on therequest, wherein at least one of the plurality of resources are changedbased on the adjusted resource allocation; and employing the changedplurality of resources to subsequently index data provided for theproject.
 8. The network device of claim 7, wherein adjusting theresource allocation further comprises allocating at least one type ofadditional resource if the request indicates an increase in theplurality of resources.
 9. The network device of claim 7, whereinadjusting the resource allocation further comprises allocating less ofat least one type of resource if the change indicates a decrease in theplurality of resources.
 10. The network device of claim 7, wherein theprocessor executes further instructions to enable actions, comprising:enabling the user of the project to manually employ a control to requestscaling of at least one of the plurality of resources.
 11. The networkdevice of claim 7, wherein changing at least one of the plurality ofresources includes at least one of: changing a number of indexer serversemployed to index data for the project; changing an amount of storagefor the data store to store data for the project; changing an amount ofmemory employed to process the indexing of data for the project; orchanging an amount of processors employed to process the indexing ofdata for the project.
 12. The network device of claim 7, whereinchanging at least one of the plurality of resources includes at leastone of: activating at least one previously deactivated indexer server bymarking at least one read-only indexer server as a read and writeindexer server; or deactivating at least one indexer server by markingthe at least one indexer server as read-only.
 13. A system for managingresources, comprising: at least one network device, comprising: a memoryfor storing data and instructions; and a processor that executes theinstructions to enable actions, comprising: determining a resourceallocation for indexing data provided for a project for each of aplurality of resources, wherein the resources includes at least oneindexer server that indexes the provided data and a data store thatstores the indexed data; providing a request from a user to scale atleast one of the plurality of resources; adjusting the resourceallocation for at least one of the plurality of resources based on therequest, wherein at least one of the plurality of resources are changedbased on the adjusted resource allocation; and employing the changedplurality of resources to subsequently index data provided for theproject.
 14. The system of claim 13, wherein adjusting the resourceallocation further comprises allocating at least one type of additionalresource if the request indicates an increase in the plurality ofresources.
 15. The system of claim 13, wherein adjusting the resourceallocation further comprises allocating less of at least one type ofresource if the change indicates a decrease in the plurality ofresources.
 16. The system of claim 13, wherein the processor executesfurther instructions to enable actions, comprising: enabling the user ofthe project to manually employ a control to request scaling of at leastone of the plurality of resources.
 17. The system of claim 13, whereinchanging at least one of the plurality of resources includes at leastone of: changing a number of indexer servers employed to index data forthe project; changing an amount of storage for the data store to storedata for the project; changing an amount of memory employed to processthe indexing of data for the project; or changing an amount ofprocessors employed to process the indexing of data for the project. 18.The system of claim 13, wherein changing at least one of the pluralityof resources includes at least one of: activating at least onepreviously deactivated indexer server by marking at least one read-onlyindexer server as a read and write indexer server; or deactivating atleast one indexer server by marking the at least one indexer server asread-only.
 19. A processor readable non-transitory storage media thatincludes instructions for managing resources, comprising: determining aresource allocation for indexing data provided for a project for each ofa plurality of resources, wherein the resources includes at least oneindexer server that indexes the provided data and a data store thatstores the indexed data; providing a request from a user to scale atleast one of the plurality of resources; adjusting the resourceallocation for at least one of the plurality of resources based on therequest, wherein at least one of the plurality of resources are changedbased on the adjusted resource allocation; and employing the changedplurality of resources to subsequently index data provided for theproject.
 20. The media of claim 19, wherein adjusting the resourceallocation further comprises allocating at least one type of additionalresource if the request indicates an increase in the plurality ofresources.
 21. The media of claim 19, wherein adjusting the resourceallocation further comprises allocating less of at least one type ofresource if the change indicates a decrease in the plurality ofresources.
 22. The media of claim 19, further comprising: enabling theuser of the project to manually employ a control to request scaling ofat least one of the plurality of resources.
 23. The media of claim 19,wherein changing at least one of the plurality of resources includes atleast one of: changing a number of indexer servers employed to indexdata for the project; changing an amount of storage for the data storeto store data for the project; changing an amount of memory employed toprocess the indexing of data for the project; or changing an amount ofprocessors employed to process the indexing of data for the project. 24.The media of claim 19, wherein changing at least one of the plurality ofresources includes at least one of: activating at least one previouslydeactivated indexer server by marking at least one read-only indexerserver as a read and write indexer server; or deactivating at least oneindexer server by marking the at least one indexer server as read-only.